How Trade Size and Frequency Affect Bid–Ask Spreads
Summary
The document asks how the size and frequency of bond trades affect subsequent bid–ask spreads. It frames the problem as a market microstructure question: trading can change liquidity, supply and demand, and sentiment, while the size of the effect is difficult to predict with a simple rule. It suggests that spreads may depend on dealers’ ability to hedge, security volatility, and the size and frequency of dealer quotes.
The responses point to empirical analysis. They note that large or frequent trades can temporarily widen spreads and move observed transaction prices, with trades around new information potentially facing wider spreads. For estimation, the document proposes collecting explanatory variables and using regression or machine learning to assess their explanatory power; it also mentions perturbation methods and compound autoregressive Poisson processes as possible approaches. The discussion offers no fitted model or empirical results, and the relevant variables and effects may differ across markets. It directs readers toward market microstructure research, including work on Treasury trading and broader equities literature.
Key ideas
- Trade size and frequency may affect liquidity and subsequent bid–ask spreads.
- Dealer hedging capacity, volatility, and quote activity are proposed as explanatory factors.
- Large or frequent trades can temporarily widen spreads and move transaction prices.
- Empirical models can compare candidate factors using regression or machine learning.
- The document provides research directions rather than a calibrated estimate or tested method.
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Full text
# Impact on bid/offer due to volume/size of trades placed # Impact on bid/offer due to volume/size of trades placed When observing bid/offer in the market I came across a question. How much trading a bond would impact its spread for subsequent trades ie. what is the impact on bid/offer due to volume/size of recently palced trades. The size of trades placed in market with impact the liquidity , demand supply , market sentiment etc. I know it is hard to predict how much the spreads will move after a trade /trades of specific size are placed in market. But is there is reasonble assumption that practitioners make ? Any pointers on existing research will be great too . EDIT : This is indeed a very hard thing to compute. This is not an extensive list of explanatory variables but one can say that – - Spreads will be inversely related to the market maker's ability to hedge his positions - Spreads will be directly related to volatility of the security - Spreads will be directly related size and frequency of quotes from Market makers. Some aggregation using ALL QUOTES of Bloomberg should help us estimate this. I believe that we can model such a behaviour by a. Either perturbation based approach such as http://www.maths.univ-evry.fr/prepubli/342.pdf b. Compound Autoregressive possion’s process. If I have something worked out , I will share the results. In the meantime if you have methodology that you use as a practitioner please do share . Thanks ## Answer by QuantK (score 2) https://quant.stackexchange.com/a/16431 You should turn to market microstructure research. Large and frequent trades can temporarily increase the spread and observed transaction price. Additionaly, trades done near the release of new information ( macro news, firms news,...) most likely need to overcome larger spreads. ## Answer by LazyCat (score 2) https://quant.stackexchange.com/a/18132 If you are after treasuries, you can check http://www.newyorkfed.org/research/staff_reports/sr381.pdf which discusses trade impact on BrokerTec. If you are after equities, the literature is enormous, you can pretty much google for "trade impact limit order book" or smth similar. In practice, it's an empirical approach: you put all the factors, that seem important, run regression or some ML algo on it, and pick the factors, that have most explanatory power.
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